拖拉机
牵引(地质)
汽车工程
压舱物
工程类
耕作
牵引力控制系统
轴
犁
控制理论(社会学)
模拟
计算机科学
结构工程
机械工程
电气工程
控制(管理)
人工智能
生态学
生物
农学
作者
Shengli Zhang,Wen Ren,Bin Xie,Zhenhao Luo,Changkai Wen,Zhongju Chen,Zhen Zhu,Tonghui Li
标识
DOI:10.1016/j.compag.2023.107750
摘要
Agricultural tractors are significant agricultural power machines that must be equipped with different implements according to tillage requirements and operate in a complex field environment. Aiming at the problem that the traditional traction control system could not balance the agronomic requirements of tillage and high-efficiency operation, this study proposed a combined control method of traction and ballast based on load transfer. This method was used for electric tractors with a battery position adjustment (BPA) structure. The tractor-implement system model was built to calculate the dynamic loads of front and rear axles accurately. Then, a multi-objective optimization function for traction performance was constructed, and the multi-objective particle swarm algorithm was employed to solve the optimal battery pack target position. The tractor controller real-time measured the draught force and battery position data. Based on the combined control strategy, the battery pack position and the tillage depth were adjusted to accomplish the cooperative control of the active ballast system and the electro-hydraulic hitch system. Finally, a field test platform for the electric tractor was developed. Ploughing tests under the traction control method and combined control method were performed. The test results showed that the tillage depth uniformity and traction performance under the combined control method were superior to the traction control method. In particular, compared with the traction control method, the tillage depth fluctuation range in the combined control method was reduced by 30.6%, the wheel slip was decreased by 15.1%, the traction efficiency was enhanced by 3.7% and the total motor energy loss was decreased by 4.9%. This study provides a technical reference for improving the economy of energy consumption and the uniformity of tillage depth of tractors in ploughing.
科研通智能强力驱动
Strongly Powered by AbleSci AI